Multi-Agent Coordination of Thermostatically Controlled Loads by Smart Power Sockets for Electric Demand Side Management

This article presents a multi-agent control architecture and an online optimization method based on a dynamic average consensus to coordinate the power consumption of a large population of thermostatically controlled loads (TCLs). Our objective is to penalize peaks of power demand, smooth the load profile, and enable demand-side management. The proposed architecture and methods exploit only local measurements of power consumption via smart power sockets (SPSs) with no access to their internal temperature. No centralized aggregator of information is exploited, and agents preserve their privacy by cooperating anonymously only through consensus-based distributed estimation. The interactions among devices occur through an unstructured peer-to-peer (P2P) network over the Internet. Methods for parameter identification, state estimation, and mixed logical modeling of TCLs and SPSs are included. The architecture is designed from a multi-agent and plug-and-play perspective, in which existing household appliances can interact with each other in an urban environment. Finally, a novel low-cost testbed is proposed along with numerical tests and experimental validation.